title: CDCOCA: a statistical method to define complexity dependence of co-occuring chromosomal aberrations.
abstract: BACKGROUND
  Copy number alterations (CNA) play a key role in cancer development and progression. Since more than one CNA can be detected in most tumors, frequently co-occurring genetic CNA may point to cooperating cancer related genes. Existing methods for co-occurrence evaluation so far have not considered the overall heterogeneity of CNA per tumor, resulting in a preferential detection of frequent changes with limited specificity for each association due to the high genetic instability of many samples.
  
  
  METHODS
  We hypothesize that in cancer some linkage-independent CNA may display a non-random co-occurrence, and that these CNA could be of pathogenetic relevance for the respective cancer. We also hypothesize that the statistical relevance of co-occurring CNA may depend on the sample specific CNA complexity. We verify our hypotheses with a simulation based algorithm CDCOCA (complexity dependence of co-occurring chromosomal aberrations).
  
  
  RESULTS
  Application of CDCOCA to example data sets identified co-occurring CNA from low complex background which otherwise went unnoticed. Identification of cancer associated genes in these co-occurring changes can provide insights of cooperative genes involved in oncogenesis.
  
  
  CONCLUSIONS
  We have developed a method to detect associations of regional copy number abnormalities in cancer data. Along with finding statistically relevant CNA co-occurrences, our algorithm points towards a generally low specificity for co-occurrence of regional imbalances in CNA rich samples, which may have negative impact on pathway modeling approaches relying on frequent CNA events.
authors.affiliation: Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland.
authors.forename: Nitin
authors.initials: N
authors.lastname: Kumar
authors.forename: Hubert
authors.initials: H
authors.lastname: Rehrauer
authors.forename: Haoyang
authors.initials: H
authors.lastname: Cai
authors.forename: Michael
authors.initials: M
authors.lastname: Baudis
mesh_terms: D000465:Algorithms; D002277:Carcinoma / Q000235:genetics; D002869:Chromosome Aberrations; D056915:DNA Copy Number Variations / Q000235:genetics; D053263:Gene Regulatory Networks; D006801:Humans; D020522:Lymphoma, Mantle-Cell / Q000235:genetics; D015233:Models, Statistical; D001749:Urinary Bladder Neoplasms / Q000235:genetics